tensorflow-cpu-aws

import tensorflow as tf # Verify TensorFlow installation and basic operation print("TensorFlow version:", tf.__version__) print("Is GPU available:", tf.config.list_physical_devices('GPU')) # Create a simple constant tensor hello = tf.constant('Hello from TensorFlow-CPU-AWS!') print(hello.numpy().decode('utf-8')) # Perform a basic operation a = tf.constant(10) b = tf.constant(32) print("a + b =", tf.add(a, b).numpy()) # Example with Keras (MNIST dataset) mnist = tf.keras.datasets.mnist (x_train, y_train), (x_test, y_test) = mnist.load_data() x_train, x_test = x_train / 255.0, x_test / 255.0 model = tf.keras.models.Sequential([ tf.keras.layers.Flatten(input_shape=(28, 28)), tf.keras.layers.Dense(128, activation='relu'), tf.keras.layers.Dropout(0.2), tf.keras.layers.Dense(10) ]) predictions = model(x_train[:1]).numpy() print("Sample predictions shape:", predictions.shape)